Fortnightly blog on Random Generators, Tech Community and Coding

Choosing Python for Data Generation

Building on another post about areas where Randomisation is used I look at reasons to use python tools for creating fake data.

Random Generators

Something that's always fascinated me is random generation and the tools created to utilise this to generated fictional data that can be used in testing, games, storytelling and simulation. I blog about random generators in tabletop games such as Dungeons and Dragons on another site

I like the endless possibilities and the way it can be used to explore things things that can only be imagined. More practical examples of randomisation in the tech world of it's use is in fake news and cryptography.

The side of random generation I want to explore is the generation of fake or fictional data.

Choosing Python for Creating Fake Data

Python is a good language for experimentation and making prototypes. Furthermore it's the tool of Data Science which may have a related space. Lastly I want to use tools such as Jupyter Notebooks for possibly playing around with and distributing generators..

Two main tools of interest appear to be Elizabeth and Faker and I'll be delving into these in the follow-up articles.

A Pet Generator

My objectives with exploring these tools is to build random generators using python, getting involved in the open source community at the same time as turning an interest into a possibility of future commercial opportunities.

I'll cover some tutorials, use cases and examples of both Elizabeth, Faker and any other tools that come up.

A Remote Software and Database Contractor specialised in Umbraco, Duncan works from wherever he finds himself. He is the co-organiser of the Python Exeter and Data Science Exeter meetup groups and speaks about Remote Working, Umbraco, Python and .NET
Outside of work he is keen on travel, random generation, foreign languages and good food.